Intelligent Optimization Modelling in Energy Forecasting

Accurate energy forecasting is important to facilitate the decision-making process in order to achieve higher efficiency and reliability in power system operation and security, economic energy use, contingency scheduling, the planning and maintenance of energy supply systems, and so on. In recent de...

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Auteur principal:	Hong, Wei-Chiang (auth)
Format:	Chapitre de livre
Publié:	MDPI - Multidisciplinary Digital Publishing Institute 2020
Sujets:	Ensemble Empirical Mode Decomposition Brain Storm Optimization asset management institutional investors state transition algorithm kernel ridge regression energy price hedging multi-objective grey wolf optimizer five-year project complementary ensemble empirical mode decomposition (CEEMD) active investment portfolio management Long Short Term Memory time series forecasting LEM2 improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) feature selection Markov-switching GARCH condition-based maintenance substation project cost forecasting model Gaussian processes regression deep convolutional neural network individual wind speed empirical mode decomposition (EMD) crude oil prices artificial intelligence techniques intrinsic mode function (IMF) multi-step wind speed prediction support vector regression (SVR) short term load forecasting energy futures General Regression Neural Network metamodel sparse Bayesian learning (SBL) commodities ensemble comparative analysis crude oil price forecasting electrical power load differential evolution (DE) fuzzy time series kernel learning short-term load forecasting data inconsistency rate renewable energy consumption long short-term memory energy forecasting modified fruit fly optimization algorithm forecasting combination forecasting Markov-switching weighted k-nearest neighbor (W-K-NN) algorithm hybrid model interpolation particle swarm optimization (PSO) algorithm regression diversification
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Intelligent Optimization Modelling in Energy Forecasting

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